The development of voids in solder balls in ball-grid array (BGA) assembly of electrical components is a significant problem in that it can have great impact on the reliability of the joints formed with such solder balls, and hence on the performance of such components. Void development, or “voiding,” in solder balls in a BGA may be introduced during board-level electrical component assembly.
X-ray radiation remains the preferred method for solder-joint inspection to detect, and thus permit action to correct or manage, such voiding. Current systems for solder-joint inspection take advantage of high-resolution X-ray technology.
In that regard, X-ray solder-joint inspection provides grayscale images which represent variances in the shape and thickness of a solder ball. Low density features such as voids produce lighter images than those of higher density or thickness, making it possible to quantitatively measure void volumes or void fractions. By accumulating void volume measurement data for several BGA assemblies, variations in the manufacturing process can be identified and corrected before anomalous conditions cause defects.
Current BGA inspection methods are mostly manual. Manual methods are generally superior to automated methods as far as accuracy in identifying voids. However, while superior in identifying voids, manual methods are time consuming, thus making such methods impractical for volume production inspection processes.
Current automated tools for estimating BGA void fractions are also problematic. Such tools are fairly crude, and therefore are often inaccurate or produce inconsistent results. Most automated tools use the “grey scale value” of pixels to identify voids and to estimate the area, where “brighter” pixels indicate voids. However, some areas that in fact are not voids are inaccurately identified as voids because they have brightness values that coincide with the brightness values assigned to voids. Moreover, voids may be too small for existing tools to detect, and those tools can also fail to clearly define void edges. As a result, the extent of voiding in a BGA assembly may be underestimated or overestimated.
Currently deployed systems for quantifying void volumes in BGA assembly solder balls also suffer from a number of deficiencies. More specifically, the number of parameters to be fitted for locating voids is large, and therefore may exceed the number of measurements available. This may result in systems of equations being ill-conditioned and often inconsistent, leading to slow or no convergence and artifacts in the fitted models.
Accounting for additional information, constraints and prior knowledge can also be difficult or impossible to express mathematically in common representations. As well, incorporating certain types of information, such as the fact that BGA assembly solder balls are approximately spherical with diameters falling predominantly in a narrow range and that the spacing between joints is known in advance, into a low-level representation is difficult and inefficient.
Moreover, as with manual void identification, manual void volume estimation undertaken by an operator using a cursor to measure the diameter of a void versus the diameter of a solder ball is inherently slow. Such manual estimation can also have low accuracy.
Still further, void volume quantification systems rely on various assumptions. These can include the types of voids, such as voids occurring within a solder ball or at an interface, as well as the spherical shape of voids. These assumptions can be incorrect, thereby leading to inaccurate estimations of void volumes or void fractions.
There is therefore a need for a method and system for automated BGA void volume quantification directed to many of the above-mentioned deficiencies. Such an automated method and system would address various speed, cost and quality issues associated with current manual and/or automated inspection and estimation methods.